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Derivation and Validation of a Diagnostic Prediction Tool for Interstitial Lung Disease.

Abstract：

BACKGROUND:Interstitial lung disease (ILD) results in high morbidity and health-care utilization. Diagnostic delays remain common and often occur in nonpulmonology settings. Screening for ILD in these settings has the potential to reduce diagnostic delays and improve patient outcomes. RESEARCH QUESTION:This study sought to determine whether a pulmonary function test (PFT)-derived diagnostic prediction tool (ILD-Screen) could accurately identify incident ILD cases in patients undergoing PFT in nonpulmonology settings. STUDY DESIGN AND METHODS:Clinical and physiologic PFT variables predictive of ILD were identified by using iterative multivariable logistic regression models. ILD status was determined by using a multi-reader approach. An ILD-Screen score was generated by using final regression model coefficients, with a score ≥ 8 considered positive. ILD-Screen test performance was validated in an independent external cohort and applied prospectively to PFTs over 1 year to identify incident ILD cases at our institution. RESULTS:Variables comprising the ILD-Screen were age, height, total lung capacity, FEV1, diffusion capacity, and PFT indication. The ILD-Screen showed consistent test performance across cohorts, with a sensitivity of 0.79 and a specificity of 0.83 when applied prospectively. A positive ILD-Screen strongly predicted ILD (OR, 18.6; 95% CI, 9.4-36.9) and outperformed common ILD clinical features, including cough, dyspnea, lung crackles, and restrictive lung physiology. Prospective ILD-Screen application resulted in a higher proportion of patients undergoing chest CT imaging compared with a historical control cohort (74% vs 56%, respectively; P = .003), with a significantly shorter median time to chest CT imaging (5.6 vs 21.1 months; P < .001). INTERPRETATION:The ILD-Screen showed good test performance in predicting ILD across diverse geographic settings and when applied prospectively. Systematic ILD-Screen application has the potential to reduce diagnostic delays and facilitate earlier intervention in patients with ILD.

journal_name

Chest

journal_title

Chest

authors

Pugashetti JV,Kitich A,Alqalyoobi S,Maynard-Paquette AC,Pritchard D,Graham J,Boctor N,Kulinich A,Lafond E,Foster E,Mendez C,Choudhry S,Chalaoui J,Morisset J,Kadoch M,Oldham JM

doi

10.1016/j.chest.2020.02.044

subject

Has Abstract

pub_date

2020-08-01 00:00:00

pages

620-629

issue

eissn

0012-3692

issn

1931-3543

pii

S0012-3692(20)30441-4

journal_volume

158

pub_type

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Derivation and Validation of a Diagnostic Prediction Tool for Interstitial Lung Disease.